Aspiriant Risk Managed Equity Fund Market Value
| RMEAX Fund | USD 15.14 0.01 0.07% |
| Symbol | Aspiriant |
Aspiriant Risk-managed 'What if' Analysis
In the world of financial modeling, what-if analysis is part of sensitivity analysis performed to test how changes in assumptions impact individual outputs in a model. When applied to Aspiriant Risk-managed's mutual fund what-if analysis refers to the analyzing how the change in your past investing horizon will affect the profitability against the current market value of Aspiriant Risk-managed.
| 03/20/2024 |
| 04/19/2024 |
If you would invest 0.00 in Aspiriant Risk-managed on March 20, 2024 and sell it all today you would earn a total of 0.00 from holding Aspiriant Risk Managed Equity or generate 0.0% return on investment in Aspiriant Risk-managed over 30 days. Aspiriant Risk-managed is related to or competes with Aspiriant Defensive, Aspiriant Risk-managed, Aspiriant Risk-managed, Vanguard Growth, Fidelity Total, Saat Market, and American Funds. The fund will invest at least 80 percent of its net assets in equity securities More
Aspiriant Risk-managed Upside/Downside Indicators
Understanding different market momentum indicators often help investors to time their next move. Potential upside and downside technical ratios enable traders to measure Aspiriant Risk-managed's mutual fund current market value against overall market sentiment and can be a good tool during both bulling and bearish trends. Here we outline some of the essential indicators to assess Aspiriant Risk Managed Equity upside and downside potential and time the market with a certain degree of confidence.
| Downside Deviation | 0.6105 | |||
| Information Ratio | (0.02) | |||
| Maximum Drawdown | 2.8 | |||
| Value At Risk | (0.71) | |||
| Potential Upside | 0.7792 |
Aspiriant Risk-managed Market Risk Indicators
Today, many novice investors tend to focus exclusively on investment returns with little concern for Aspiriant Risk-managed's investment risk. Other traders do consider volatility but use just one or two very conventional indicators such as Aspiriant Risk-managed's standard deviation. In reality, there are many statistical measures that can use Aspiriant Risk-managed historical prices to predict the future Aspiriant Risk-managed's volatility.| Risk Adjusted Performance | 0.075 | |||
| Jensen Alpha | 0.0175 | |||
| Total Risk Alpha | 0.005 | |||
| Sortino Ratio | (0.01) | |||
| Treynor Ratio | 0.0897 |
Sophisticated investors, who have witnessed many market ups and downs, anticipate that the market will even out over time. This tendency of Aspiriant Risk-managed's price to converge to an average value over time is called mean reversion. However, historically, high market prices usually discourage investors that believe in mean reversion to invest, while low prices are viewed as an opportunity to buy.
Aspiriant Risk Managed Backtested Returns
We consider Aspiriant Risk-managed very steady. Aspiriant Risk Managed secures Sharpe Ratio (or Efficiency) of 0.0998, which signifies that the fund had a 0.0998% return per unit of risk over the last 3 months. We have found twenty-seven technical indicators for Aspiriant Risk Managed Equity, which you can use to evaluate the volatility of the entity. Please confirm Aspiriant Risk-managed's Mean Deviation of 0.3491, downside deviation of 0.6105, and Risk Adjusted Performance of 0.075 to double-check if the risk estimate we provide is consistent with the expected return of 0.0468%. The fund shows a Beta (market volatility) of 0.56, which signifies possible diversification benefits within a given portfolio. As returns on the market increase, Aspiriant Risk-managed's returns are expected to increase less than the market. However, during the bear market, the loss of holding Aspiriant Risk-managed is expected to be smaller as well.
Auto-correlation | 0.58 |
Modest predictability
Aspiriant Risk Managed Equity has modest predictability. Overlapping area represents the amount of predictability between Aspiriant Risk-managed time series from 20th of March 2024 to 4th of April 2024 and 4th of April 2024 to 19th of April 2024. The more autocorrelation exist between current time interval and its lagged values, the more accurately you can make projection about the future pattern of Aspiriant Risk Managed price movement. The serial correlation of 0.58 indicates that roughly 58.0% of current Aspiriant Risk-managed price fluctuation can be explain by its past prices.
| Correlation Coefficient | 0.58 | |
| Spearman Rank Test | 0.2 | |
| Residual Average | 0.0 | |
| Price Variance | 0.02 |
Aspiriant Risk Managed lagged returns against current returns
Autocorrelation, which is Aspiriant Risk-managed mutual fund's lagged correlation, explains the relationship between observations of its time series of returns over different periods of time. The observations are said to be independent if autocorrelation is zero. Autocorrelation is calculated as a function of mean and variance and can have practical application in predicting Aspiriant Risk-managed's mutual fund expected returns. We can calculate the autocorrelation of Aspiriant Risk-managed returns to help us make a trade decision. For example, suppose you find that Aspiriant Risk-managed has exhibited high autocorrelation historically, and you observe that the mutual fund is moving up for the past few days. In that case, you can expect the price movement to match the lagging time series.
Current and Lagged Values |
| Timeline |
Aspiriant Risk-managed regressed lagged prices vs. current prices
Serial correlation can be approximated by using the Durbin-Watson (DW) test. The correlation can be either positive or negative. If Aspiriant Risk-managed mutual fund is displaying a positive serial correlation, investors will expect a positive pattern to continue. However, if Aspiriant Risk-managed mutual fund is observed to have a negative serial correlation, investors will generally project negative sentiment on having a locked-in long position in Aspiriant Risk-managed mutual fund over time.
Current vs Lagged Prices |
| Timeline |
Aspiriant Risk-managed Lagged Returns
When evaluating Aspiriant Risk-managed's market value, investors can use the concept of autocorrelation to see how much of an impact past prices of Aspiriant Risk-managed mutual fund have on its future price. Aspiriant Risk-managed autocorrelation represents the degree of similarity between a given time horizon and a lagged version of the same horizon over the previous time interval. In other words, Aspiriant Risk-managed autocorrelation shows the relationship between Aspiriant Risk-managed mutual fund current value and its past values and can show if there is a momentum factor associated with investing in Aspiriant Risk Managed Equity.
Regressed Prices |
| Timeline |
Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Aspiriant Risk-managed in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Aspiriant Risk-managed's short interest history, or implied volatility extrapolated from Aspiriant Risk-managed options trading.
Currently Active Assets on Macroaxis
Check out Aspiriant Risk-managed Correlation, Aspiriant Risk-managed Volatility and Aspiriant Risk-managed Alpha and Beta module to complement your research on Aspiriant Risk-managed. Note that the Aspiriant Risk Managed information on this page should be used as a complementary analysis to other Aspiriant Risk-managed's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Funds Screener module to find actively-traded funds from around the world traded on over 30 global exchanges.
Aspiriant Risk-managed technical mutual fund analysis exercises models and trading practices based on price and volume transformations, such as the moving averages, relative strength index, regressions, price and return correlations, business cycles, fund market cycles, or different charting patterns.